Nigeria Unveils YarnGPT: Pioneering Localized AI Models for Nigerian Languages
Thank you for reading this post, don't forget to subscribe!Nigeria is making strides in AI development with the release of YarnGPT, a groundbreaking family of large language models designed to address the unique challenges of Nigerian English accents and local languages.
YarnGPT comprises two open-source text-to-speech models: one tailored to Nigerian-accented English (YarnGPT) and another focused on the country’s native languages—Igbo, Yoruba, and Hausa (YarnGPT-local). These models, built on the SmolLM2-360M architecture from Hugging Face, were trained entirely on Google Colab.
In a bid to promote collaboration and innovation, the models and their training code are being made open-source. This allows developers to experiment and expand upon this work, helping to foster a more localized AI ecosystem.
• YarnGPT: Link
• YarnGPT-local: Link
• GitHub Repo: Link
The launch of YarnGPT comes at a crucial time as Nigeria seeks to bridge the gap in AI technology adoption and local language representation. This initiative is a part of the country’s broader push to enhance its AI capabilities and contribute to the global open-source community.
The Hugging Face team’s commitment to open-source AI has been instrumental in making this project possible, and contributions from the broader AI community continue to drive its success. The release aims to create a more inclusive tech landscape and promote the development of AI that truly reflects the diversity of languages and accents in Nigeria.
Developers and AI enthusiasts are encouraged to explore the model repositories, test the models, and share feedback to help refine and improve the models for real-world applications.
